Longlong Yang

Genome-wide analysis of human HSF1 signaling reveals a transcriptional program linked to cellular adaptation and survival

Although HSF1 plays an important role in the cellular response to proteotoxic stressors, little is known about the structure and function of the human HSF1 signaling network under both stressed and unstressed conditions. In this study, we used a combination of chromatin immunoprecipitation microarray analysis and time course gene expression microarray analysis with and without siRNA-mediated inhibition of HSF1 to comprehensively identify genes regulated directly and indirectly by HSF1. The correlation between promoter binding and gene expression was not significant for all genes bound by HSF1, suggesting that HSF1 binding per se is not sufficient for expression. However, the correlation with promoter binding was significant for genes identified as HSF1-regulated following siRNA knockdown. Among promoters bound by HSF1 following heat shock, a gene ontology analysis showed significant enrichment only in categories related to protein folding. In contrast, analysis of the extended HSF1 signaling network following siRNA knockdown showed enrichment in a variety of categories related to protein folding, anti-apoptosis, RNA splicing, ubiquitinylation and others, highlighting a complex transcriptional program regulated directly and indirectly by HSF1.

BMDExpress: a software tool for the benchmark dose analyses of genomic data

BackgroundDose-dependent processes are common within biological systems and include phenotypic changes following exposures to both endogenous and xenobiotic molecules. The use of microarray technology to explore the molecular signals that underlie these dose-dependent processes has become increasingly common; however, the number of software tools for quantitatively analyzing and interpreting dose-response microarray data has been limited.ResultsWe have developed BMDExpress, a Java application that combines traditional benchmark dose methods with gene ontology classification in the analysis of dose-response data from microarray experiments. The software application is designed to perform a stepwise analysis beginning with a one-way analysis of variance to identify the subset of genes that demonstrate significant dose-response behavior. The second step of the analysis involves fitting the gene expression data to a selection of standard statistical models (linear, 2° polynomial, 3° polynomial, and power models) and selecting the model that best describes the data with the least amount of complexity. The model is then used to estimate the benchmark dose at which the expression of the gene significantly deviates from that observed in control animals. Finally, the software application summarizes the statistical modeling results by matching each gene to its corresponding gene ontology categories and calculating summary values that characterize the dose-dependent behavior for each biological process and molecular function. As a result, the summary values represent the dose levels at which genes in the corresponding cellular process show transcriptional changes.ConclusionThe application of microarray technology together with the BMDExpress software tool represents a useful combination in characterizing dose-dependent transcriptional changes in biological systems. The software allows users to efficiently analyze large dose-response microarray studies and identify reference doses at which particular cellular processes are altered. The software is freely available at http://sourceforge.net/projects/bmdexpress/ and is distributed under the MIT Public License.

Dose-dependent transitions in Nrf2-mediated adaptive response and related stress responses to hypochlorous acid in mouse macrophages.

Hypochlorous acid (HOCl) is potentially an important source of cellular oxidative stress. Human HOCl exposure can occur from chlorine gas inhalation or from endogenous sources of HOCl, such as respiratory burst by phagocytes. Transcription factor Nrf2 is a key regulator of cellular redox status and serves as a primary source of defense against oxidative stress. We recently demonstrated that HOCl activates Nrf2-mediated antioxidant response in cultured mouse macrophages in a biphasic manner. In an effort to determine whether Nrf2 pathways overlap with other stress pathways, gene expression profiling was performed in RAW 264.7 macrophages exposed to HOCl using whole genome mouse microarrays. Benchmark dose (BMD) analysis on gene expression data revealed that Nrf2-mediated antioxidant response and protein ubiquitination were the most sensitive biological pathways that were activated in response to low concentrations of HOCl (<0.35 mM). Genes involved in chromatin architecture maintenance and DNA-dependent transcription were also sensitive to very low doses. Moderate concentrations of HOCl (0.35 to 1.4 mM) caused maximal activation of the Nrf2 pathway and innate immune response genes, such as IL-1beta, IL-6, IL-10 and chemokines. At even higher concentrations of HOCl (2.8 to 3.5 mM) there was a loss of Nrf2-target gene expression with increased expression of numerous heat shock and histone cluster genes, AP-1-family genes, cFos and Fra1 and DNA damage-inducible Gadd45 genes. These findings confirm an Nrf2-centric mechanism of action of HOCl in mouse macrophages and provide evidence of interactions between Nrf2, inflammatory, and other stress pathways.

Temporal concordance between apical and transcriptional points of departure for chemical risk assessment.

The number of legacy chemicals without toxicity reference values combined with the rate of new chemical development is overwhelming the capacity of the traditional risk assessment paradigm. More efficient approaches are needed to quantitatively estimate chemical risks. In this study, rats were dosed orally with multiple doses of six chemicals for 5 days and 2, 4, and 13 weeks. Target organs were analyzed for traditional histological and organ weight changes and transcriptional changes using microarrays. Histological and organ weight changes in this study and the tumor incidences in the original cancer bioassays were analyzed using benchmark dose (BMD) methods to identify noncancer and cancer points of departure. The dose-response changes in gene expression were also analyzed using BMD methods and the responses grouped based on signaling pathways. A comparison of transcriptional BMD values for the most sensitive pathway with BMD values for the noncancer and cancer apical endpoints showed a high degree of correlation at all time points. When the analysis included data from an earlier study with eight additional chemicals, transcriptional BMD values for the most sensitive pathway were significantly correlated with noncancer (r = 0.827, p = 0.0031) and cancer-related (r = 0.940, p = 0.0002) BMD values at 13 weeks. The average ratio of apical-to-transcriptional BMD values was less than two, suggesting that for the current chemicals, transcriptional perturbation did not occur at significantly lower doses than apical responses. Based on our results, we propose a practical framework for application of transcriptomic data to chemical risk assessment.

Integrating pathway-based transcriptomic data into quantitative chemical risk assessment: a five chemical case study.

The traditional approach for performing a chemical risk assessment is time and resource intensive leading to a limited number of published assessments on which to base human health decisions. In comparison, most contaminated sites contain chemicals without published reference values or cancer slope factors that are not considered quantitatively in the overall hazard index calculation. The integration of transcriptomic technology into the risk assessment process may provide an efficient means to evaluate quantitatively the health risks associated with data poor chemicals. In a previous study, female B6C3F1 mice were exposed to multiple concentrations of five chemicals that were positive for lung and/or liver tumor formation in a two-year rodent cancer bioassay. The mice were exposed for a period of 13 weeks and the target tissues were analyzed for traditional histological and organ weight changes and transcriptional changes using microarrays. In this study, the dose-response changes in gene expression were analyzed using a benchmark dose (BMD) approach and the responses grouped based on pathways. A comparison of the transcriptional BMD values with those for the traditional non-cancer and cancer apical endpoints showed a high degree of correlation for specific pathways. Many of the correlated pathways have been implicated in non-cancer and cancer disease pathogenesis. The results demonstrate that transcriptomic changes in pathways can be used to estimate non-cancer and cancer points-of-departure for use in quantitative risk assessments and have identified potential toxicity pathways involved in chemically induced mouse lung and liver responses.

A functional map of NFκB signaling identifies novel modulators and multiple system controls

BackgroundThe network of signaling pathways that leads to activation of the NFκB transcription factors is a branched structure with different inputs and cross-coupling with other signaling pathways. How these signals are integrated to produce specific, yet diverse responses is not clearly understood. To identify the components and structural features of the NFκB network, a series of cell-based, genomic screens was performed using a library of approximately 14,500 full-length genes.ResultsA total of 154 positive and 88 negative modulators of NFκB signaling were identified. Using a series of dominant-negative constructs and functional assays, these modulators were mapped to the known NFκB signaling cascade. Most of the positive modulators acted upstream of the IκB kinase complex, supporting previous observations that the IκB kinases represent the primary point of convergence in the network. A number of negative modulators were localized downstream of the IκB kinase β (IKBKB) subunit, suggesting that they form an additional layer of negative control within the system. The expression of the modulators at the RNA level was distributed disproportionately across tissues, providing flexibility in network structure, and the number of positive and negative modulators present in a given tissue was highly correlated, suggesting that positive and negative regulation is balanced at the tissue level.ConclusionThe relative locations of the modulators are consistent with an hourglass structure for the NFκB network that is characteristic of robust systems. The tissue distribution of the modulators and downstream location of the negative modulators serve as layers of control within the system that allow differential responses to different stimuli.

The Aryl-Hydrocarbon Receptor Protein Interaction Network (AHR-PIN) as Identified by Tandem Affinity Purification (TAP) and Mass Spectrometry

The aryl-hydrocarbon receptor (AHR), a ligand activated PAS superfamily transcription factor, mediates most, if not all, of the toxicity induced upon exposure to various dioxins, dibenzofurans, and planar polyhalogenated biphenyls. While AHR-mediated gene regulation plays a central role in the toxic response to dioxin exposure, a comprehensive understanding of AHR biology remains elusive. AHR-mediated signaling starts in the cytoplasm, where the receptor can be found in a complex with the heat shock protein of 90 kDa (Hsp90) and the immunophilin-like protein, aryl-hydrocarbon receptor-interacting protein (AIP). The role these chaperones and other putative interactors of the AHR play in the toxic response is not known. To more comprehensively define the AHR-protein interaction network (AHR-PIN) and identify other potential pathways involved in the toxic response, a proteomic approach was undertaken. Using tandem affinity purification (TAP) and mass spectrometry we have identified several novel protein interactions with the AHR. These interactions physically link the AHR to proteins involved in the immune and cellular stress responses, gene regulation not mediated directly via the traditional AHR:ARNT heterodimer, and mitochondrial function. This new insight into the AHR signaling network identifies possible secondary signaling pathways involved in xenobiotic-induced toxicity.